Abstract LB-021: Combination of quantitative histomorphometry with NFκB/p65 nuclear localization is better predictor of biochemical recurrence in prostate cancer patients

Clinical management decisions in prostate cancer are often based on risk determination with major uncertainty since limited tools are available to understand the risk of disease progression and guide the treatment decision process. Computer-aided quantitative histomorphometric analysis has emerged as a powerful computing tool to identify, characterize, and quantitate histologic features of tissues beyond human visual capabilities. Several quantitative features can be assessed, such as precise numeric measurements pertaining to the spatial arrangement and architecture of nuclei, shapes of nests and nuclei, and nuclear texture. This technology has proven to be useful for the detection of cancer in tissue sections and also for predicting tumor biology and clinical outcome in cancer patients. Utilizing a combination of synergistic strategy of quantitative histomorphometry and biomarker expression of NF-κB/p65 from prostate tissue specimens, we sought to fuse structural and functional information from morphological and molecular markers to better characterize disease progression improving prediction of biochemical recurrence (BCR). Here we utilized radical prostatectomy specimens (n=23) for feature extraction from 15 patients without BCR and 8 patients who experienced BCR (PSA > 0.2 ng/ml) within two years of surgery. Digitized HE 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr LB-021.